CylanceOPTICS is easy to use.
The product's technical support is slow.
I have been using the product for three years.
CylanceOPTICS is easy to use.
I rate the solution a nine out of ten.
Kaspersky Anti-Targeted Attack Platform and CylanceOPTICS compete in advanced cybersecurity. Kaspersky has an edge in pricing and support, while CylanceOPTICS leads with superior features due to its AI technology.
Features: Kaspersky Anti-Targeted Attack Platform offers robust threat detection, detailed reporting capabilities, and user-friendly integration. CylanceOPTICS provides AI-driven threat prevention, low system impact, and real-time incident response.
Room for Improvement: Kaspersky needs to simplify its integration processes, improve UI/UX, and enhance scalability options. CylanceOPTICS requires better documentation, faster response times, and improved customer training resources.
Ease of Deployment and Customer Service: Kaspersky is noted for its straightforward deployment and dedicated support. CylanceOPTICS has a smooth deployment process but lacks immediate support responses.
Pricing and ROI: Kaspersky offers reasonable pricing with good ROI. CylanceOPTICS has higher upfront costs but is seen to offer better long-term value due to its advanced features.
Our cloud-native BlackBerry® Optics provide visibility, on-device threat detection and remediation across your organization. In milliseconds. And our EDR approach effectively and efficiently hunts threats while eliminating response latency. It’s the difference between a minor security event—and one that’s widespread and uncontrolled.
Today’s cybercriminals constantly design unique and innovative methods of penetration and compromise. To avoid perimeter prevention technologies they use social engineering, non-malware and supply chain attacks to operate under the radar of security designed to catch ‘bad’ traces. It’s not enough to just ‘know’ what’s bad or dangerous – enterprises need to understand what’s normal, and use AI-driven techniques that simplify and automate this process. Targeted Attack Analyzer is a machine learning engine that involves self-learning to establish the baseline of normal, legitimate activities of an entire network. Through continuous network telemetry collection it finds deviations, detects suspicious activities and predicts further malicious actions at the initial stages of multilayered attacks.
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